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May 17, 2014 · In this paper, we provide a new P2P traffic identification method based on active learning and show its feasibility and effectiveness by ...
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To overcome the sample labeling problem, a new P2P traffic identification approach by active learning called P2PTIAL is presented. P2PTIAL is composed of two ...
To overcome the sample labeling problem, a new P2P traffic identification approach by active learning called P2PTIAL is presented. P2PTIAL is composed of ...
To overcome the sample labeling problem, a new P2P traffic identification approach by active learning called P2PTIAL is presented. P2PTIAL is composed of two ...
Bibliographic details on Active learning for P2P traffic identification.
BibTeX key: journals/ppna/LiuS15; entry type: article; year: 2015; journal: Peer-to-Peer Netw. Appl. number: 5; pages: 733-740; volume: 8 ...
algorithms to automate the classifica- tion process, discover different traffic patterns produced by de- vices, and classify encrypted traffic.
In this section, we propose a multiclass imbalance and concept drift network traffic classification framework based on online active learning (MicFoal). The ...
Nov 18, 2021 · This study investigates the applicability of an active form of ML, called Active Learning (AL), in NTC. AL reduces the need for a large number ...
Mar 8, 2022 · Abstract—Network Traffic Classification (NTC) has become an important feature in various network management operations,.